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Visualization of Scene Structure Uncertainty in Multi-View Reconstruction

Visualization of Scene Structure Uncertainty in Multi-View Reconstruction. Shawn Recker 1 , Mauricio Hess-Flores 1 , Mark A. Duchaineau 2 , and Kenneth I. Joy 1. 1 University of California, Davis, USA, { strecker , mhessf , joy}@ucdavis.edu 2 Google, Inc. duchaineau@google.com.

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Visualization of Scene Structure Uncertainty in Multi-View Reconstruction

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  1. Visualization of Scene Structure Uncertainty in Multi-View Reconstruction Shawn Recker1, Mauricio Hess-Flores1, Mark A. Duchaineau2, and Kenneth I. Joy1 1University of California, Davis, USA, {strecker, mhessf, joy}@ucdavis.edu 2Google, Inc. duchaineau@google.com Applied Imagery Pattern Recognition (AIPR) Workshop 2012 Washington, DC October 9-11, 2012

  2. Multi-View Reconstruction Bundle Adjustment ‘dinosaur’ dataset images from [1].

  3. Structural Uncertainty Visualization

  4. Volume Visualization 5 6 4 Volume Rendering 5 3 4 2 3 4 4 5 3 4 2 3 1 2 3 3 4 2 Contouring 3 1 2 1 2 0

  5. Procedure …

  6. Evaluated Test Cases • Simulation test cases • Frame decimation simulation • Feature matching inaccuracy • Self calibration tests • Comparison test cases

  7. Frame Decimation Graphs

  8. Frame Decimation Results 10 cameras 15 cameras 30 cameras 8 cameras 4 cameras 2 cameras

  9. Feature Tracking Graphs

  10. Feature Tracking Inaccuracy Results 1% Error 0% Error 2% Error 5% Error 10% Error 20% Error

  11. Reprojection Error versus Angular Error Reprojection Error Angular Error

  12. Conclusions and Future Work • Presentation of a structural uncertainty visualization tool • Continued visualization of computer vision • Investigation of our cost function • Scene structure computation • Camera pose estimation

  13. Acknowledgements • This work was supported in part by Lawrence Livermore National Laboratory and the National Nuclear Security Agency through Contract No. DE-FG52-09NA29355

  14. References [1] Oxford Visual Geometry Group, “Multi-view and Oxford Colleges building reconstruction,” August 2009. [2] V. Rodehorst, M. Heinrichs, and O. Hellwich, “Evaluation of relative pose estimation methods for multi-camera setups,” in International Archives of Photogrammetry and Remote Sensing (ISPRS ’08), (Beijing, China), pp. 135–140, 2008. [3] D. Knoblauch, M. Hess-Flores, M. A. Duchaineau, and F. Kuester, “Factorization of correspondence and camera error for unconstrained dense correspondence applications,” in 5th International Symposium on Visual Computing, pp. 720–729, 2009. [4] T. Torsney-Weir, A. Saad, T. M´’oller, H.-C. Hege, B. Weber, and J.-M. Verbavatz, “Tuner: Principledparameterfindingforimagesegmentationalgorithmsusing visual response surfaceexploration,” IEEE Trans. OnVisualizationand ComputerGraphics, vol. 17, no. 12, pp. 1892–1901, 2011. [5] A. Saad, T. M´’oller, and G. Hamarneh, “Probexplorer: Uncertaintyguidedexplorationand editing of probabilistic medical imagesegmentation,” Computer Graphics Forum, vol. 29, no. 3, pp. 1113–1122, 2010.

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